Scientific Core

科学核心

• 批准号: 10377561
• 负责人: LINGXIN HAO
• 金额: $ 21.24万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-10 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10377561
• 关键词: Address; Adoption; African; Age; Area; Bayesian Modeling; Biological Markers; Biometry; COVID-19 pandemic; Cohort Studies; Computers; Consultations; Country; Data; Data Analyses; Data Analytics; Data Collection; Data Science; Data Sources; Development; Educational workshop; Event; Fertilization; Funding; Goals; Growth; Health Sciences; High Performance Computing; Influentials; Lead; Link; Mathematics; Measurement; Memory; Methodology; Methods; Modeling; Output; Population; Population Dynamics; Population Process; Population Sciences; Postdoctoral Fellow; Production; Productivity; Program Development; Public Health; Publications; Research; Resources; Series; Services; South Asian; Survey Methodology; Surveys; Techniques; Time; Universities; Work; career; data acquisition; data management; design; digital; econometrics; improved; innovation; laptop; programs; simulation; social; sociodemographics; synergism

Scientific Core Abstract The primary goal of the Scientific Core is to enhance the scientific impact, innovation, and productivity of Hopkins Population Center (HPC) Associates’ research by facilitating the expansion of existing research, initiation of new research directions, cross-fertilization across HPC Primary Research Areas (PRAs), successful attainment of competitive external funding, and production of influential publications. The HPC Director, Dr. Lingxin Hao, also directs the Scientific Core. Dr. Ciprian Crainiceanu is the Methods Lead, and Dr. Qingfeng Li is the Data Lead. The Scientific core includes a part-time technical staff and a graduate RA. The Scientific Core provides three types of services: Methods, Data, and Computing. Specifically, the Methods Support facilitates the adoption of advanced methods to enhance the rigor of population dynamics research in three topics: (1) Advanced Data Analytics address the fusion between data science, population science, and health science, focusing on innovative analytics of wearable data, biomarkers, and population-scale networks available in surveys or cohort studies; (2) Advanced Demographic Measurement and Modeling methods enhance population dynamics research, focusing on advanced demographic measurement, Bayesian modeling, and causal inferences; and (3) Data Collection Methods in the 21st Century focuses on innovative data collection methods such as digital survey methods, long-term panel surveys, assessing and achieving population representativeness, and innovative combination of qualitative data and econometrics. The Scientific Core provides Methods Support via Methodological Consultation for developing new projects and analyzing data supported by a Methodological Improvement Fund (MIF) program and Informal Educational Programs. The Data Support includes timely data acquisition and management for new demographic events and changing population processes, including the COVID-19 pandemic. The Computing Support maintains a “Cold Room” for confidential data use and a server with a large memory and voluminous workspace. The Scientific Core, jointly with the Development Core and Administrative Core, provides concerted nurturing of Early-Career Associates to put them on fast track to independence. The P2C funding will allow the Scientific Core to provide targeted, efficient services to HPC Associates and maximize the HPC’s scientific output through a close synergy with the Development Core and Administrative Core, linking HPC Associates’ methodological needs with methodological expertise within and beyond Johns Hopkins University (JHU) and leveraging the resources of JHU’s data science units.

科学核心摘要 科学核心的主要目标是提高科学的影响力，创新和生产力， 霍普金斯人口中心（HPC）协会的研究，促进扩大现有的研究， 启动新的研究方向，跨HPC主要研究领域（PRA）的交叉施肥， 成功获得竞争性外部资金，并出版有影响力的出版物。的HPC 主任，郝凌新博士，也指导科学核心。Ciprian Crainiceanu博士是方法负责人， 李清风是数据负责人。科学核心包括兼职技术人员和研究生RA。的 Scientific Core提供三种类型的服务：方法、数据和计算。具体而言，方法 支持促进采用先进的方法，以提高人口动态研究的严谨性， 三个主题：（1）高级数据分析解决数据科学，人口科学和 健康科学，专注于可穿戴数据，生物标志物和人口规模网络的创新分析 可用于调查或队列研究;（2）先进的人口统计测量和建模方法 加强人口动态研究，重点是先进的人口统计测量，贝叶斯 建模和因果推理;（3）21世纪的数据收集方法侧重于创新 数据收集方法，如数字调查方法、长期小组调查、评估和实现 人口代表性，以及定性数据和计量经济学的创新结合。科学 核心通过方法咨询为开发新项目和分析提供方法支持 数据由方法改进基金（MIF）计划和非正式教育计划支持。 数据支持包括针对新的人口统计事件及时获取和管理数据， 不断变化的人口进程，包括COVID-19大流行。计算支持保持“冷 用于机密数据使用的“空间”和一台具有大内存和大量工作空间的服务器。科学 核心与发展核心和行政核心一起，为早期职业生涯提供协调一致的培养， 帮助他们走上独立的快车道。P2C资金将允许科学核心提供 为HPC Associates提供有针对性的高效服务，并通过密切合作， 与开发核心和管理核心协同，将HPC Associates的方法需求联系起来 拥有约翰霍普金斯大学（JHU）内外的方法学专业知识，并利用 JHU的数据科学部门